Power plant multiagent control system
Abstract：To deal with the nonlinear multi-variable and multiple control objective characteristic of power plant, the power plant multiagent control system (PPMACS) is designed. In the PPMACS, the feedforward control agents (FFCAs) make decisions using the neuro-fuzzy systems and the feedback control agents (FBCAs) make decisions using the genetic algorithm-based fuzzy systems. The optimal task decomposition agents (OTDAs) optimlly decompose the task of the PPMACS through an optimization agent and a decomposition agent. The coordinator agent (COA) coordinates the agents in the PPMACS according to different operating conditions. Simulation results demonstrate that the PPMACS implement the multiobjective operation and wide range load tracking. Neural netwroks, fuzzy logic and genetic algorithm are effective tools for the agents of the PPMACS in making decisions.
Keywords：decision-makingfeedback controlfeedforward controlfuzzy logicgenetic algorithmsmultiagent control systemneural networks
Publication Date：2004-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 405-410 )